Human activities recognition in smart living environment
Human activity recognition has been changing the way people live through smart homes. Machine learning algorithms are used to accurately detect human activities at home. The usage of cameras can be considered invasive to some home owners, therefore alternate kind of sensors have to be used. Mobil...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/75269 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Human activity recognition has been changing the way people live through smart
homes. Machine learning algorithms are used to accurately detect human
activities at home. The usage of cameras can be considered invasive to some
home owners, therefore alternate kind of sensors have to be used. Mobile phones
provide a good range of sensors to test and also to detect the various types of
activities.
This paper examines different data sets for comparison, how accelerometer,
gyroscope as well as pressure sensors cam be used in detecting the various
activities. MATLAB’s classificationLearner application will be used in this
experiment to aid in quick and accurate testing, as well as visualising of data |
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